This is nice and fun for getting some fast indications on an unknown codebase, but, as others said here and elsewhere, it doesn't replace human-made documentation.

https://passo.uno/whats-wrong-ai-generated-docs/

My bet is that the combination of humans and language models is stronger than humans alone or models alone. In other words there's a virtuous cycle developing where the codebases that embrace machine documentation tools end up getting higher quality docs in the long run. For example, last week I tried out a codebase summary tool. It had some inaccuracies and I knew exactly where it was pulling the incorrect data from. I fixed that data, re-ran the summarization tool, and was satisfied to see a more accurate summary. But yes, it's probably key to keep human technical writers (like myself!) in the loop.